xboost

To identify lithologies, geoscientists use subsurface data such as wireline logs and petrophysical data. However, this process is often tedious, repetitive, and time-consuming. This project aims to use machine learning techniques to predict lithology from petrophysical logs, which are direct indicators of lithology.

Machine Learning model to predict the health of the car engines using various algorithms like KNN, SVM, Random Forest, Xboost Classifier.

AI-powered supply chain decision intelligence system for shipment delay prediction, risk assessment, and optimized mitigation recommendations using XGBoost, FastAPI, React, and optimization techniques.

End-to-end project to predict basketball player points. (regression problem)

An interactive ML decision engine and Streamlit dashboard for real-time credit risk modeling, Probability of Default (PD) scoring, and portfolio expected loss analytics.

how to predict score credit to home credit indonesia with machine learning modeling, find more to Home Credit Indonesia

AI-Powered Quick Commerce Delivery Intelligence System — End-to-end analytics & ML prediction dashboard for Blinkit, Zepto, Swiggy Instamart | 9.4L orders | Random Forest R²=0.9658 | Streamlit + Plotly + XGBoost | Live Deployed

Comparison of multiple machine learning classifiers for corporate bankruptcy prediction using financial ratios, class imbalance handling, and cross‑validation.

Implemented time series forecasting to predict future orders for Glovo, utilizing models such as ARIMA/SARIMA, LASSO, XGBoost, and Linear Regression.

Credit risk prediction using machine learning with Logistic Regression, SHAP explainability, threshold optimization and XGBoost comparison.

Strona w HTML przewidująca popyt na rowery w Seoulu, porównująca wyniki modelu XBoost i regresji liniowej

Complete ML pipeline for Titanic survival prediction using Logistic Regression, Random Forest, XGBoost, and SVM includes EDA, preprocessing, tuning, and feature importance.

AI-powered real-time traffic intelligence for India

AI-powered project management assistant using ML to predict task delays, classify project risk, and optimize resource allocation. Features an NLP query interface, automated reporting, and a Streamlit dashboard. Built with FastAPI, scikit-learn, and XGBoost — runs locally, no cloud dependency required.

XGBoost vasitəsilə neftin gələcək qiymətinin proqnozlaşdırılması layihəsi

ML and data processing

Sustainability is our shared responsibility. This interface helps visualize environmental tracking, making complex carbon data clear and actionable.

Machine learning pipeline for football match outcome prediction using feature engineering, Random Forest and XGBoost models.

AI-powered Loan Approval Prediction System using Machine Learning, Flask, and XGBoost with Render deployment.